Building Prosperous Knowledge Cities
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Building Prosperous Knowledge Cities

Policies, Plans and Metrics

Edited by Tan Yigitcanlar, Kostas Metaxiotis and Francisco Javier Carrillo

This unique book reveals the procedural aspects of knowledge-based urban planning, development and assessment. Concentrating on major knowledge city building processes, and providing state-of-the-art experiences and perspectives, this important compendium explores innovative models, approaches and lessons learnt from a number of key case studies across the world.
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Chapter 19: Benchmarking: Knowledge-based Development Metrics through the MAKCi Exercise

Alicia Leal and Blanca C. Garcia


Alicia Leal and Blanca C. Garcia INTRODUCTION Researchers and practitioners have agreed that one of the difficulties in creating and sustaining knowledge cities is the lack of benchmarks to identify those cities and regions that are generating knowledge-driven initiatives, thus triggering development and collective value for their regions (Chase, 2007). In such a challenging context, some key notions have emerged in recent years to characterize such benchmarks. Following a knowledge-based development (KBD) perspective, this chapter will report on research findings obtained from statistical modelling applied to knowledge city benchmarking methodologies. The main objective is to put forward a knowledge-based taxonomy as a methodological tool to identify how tacit knowledge conversion generates quantitative intangible indicators by means of simulation and pattern modelling (Montgomery et al., 2006). For urban communities around the world, such research could provide valuable information to build their own knowledge-city quantitative taxonomy, and make comparative identifications of those key elements of knowledge-leveraging capabilities that greatly impact cities’ knowledge capital. Indeed, a parallel benchmarking difficulty is creating a city’s systemic accountable base or taxonomy once the city’s contextual benchmarks have been established. The first part of the chapter will thus depict how at this point in the benchmarking process, the Generic Capitals System (GCS) emerges as a value-based, knowledge management (KM) model that attempts a systemic, integrative perspective for city taxonomy building (Carrillo, 2002, 2004). It elicits a systematic assessment of a city’s capital base (both tangible and intangible) and its capacity to recombine it in innovative ways. The...

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